Abstract
Conventionally and theoretically increase in money supply according to the quantity theory of money triggers a high inflation rate in developed and emerging economies. The reality in Nigeria contravenes the quantity theory of money. This study investigates the missing link in Nigeria from January 2010 to December 2018 by applying the Johansen co-integration, Granger causality tests and Vector Error Correction Model (VECM) on the monthly data. The findings indicated that money supply does not cause inflation. Inflation is caused by non-monetary factors of political instability, corruption, poor basic infrastructure among others. Money supply and inflation co-integrate in the long-term. The causality test proposed a uni-directional flow from inflation to the money supply. Bi-directional causality was not observed in this study. The VECM result indicated that disequilibrium caused in the previous year can converge back to equilibrium in the current year. The general findings of the study disagreed with the quantity theory of money. The study recommends that non-monetary factors of political instability, corruption, poor basic infrastructure among others were responsible for the missing link. These factors should be checked and put in perspective to achieve low inflation at a single digit in Nigeria.
Keywords: Money supply, Inflation, Granger causality, Cointegration, VECM, Monetary policy rate.
Received: 26 March 2019 / Revised: 2 May 2019 / Accepted: 24 June 2019/ Published: 22 August 2019
Contribution/ Originality
This study contributes to the extant literature by using monthly M3 and M2 money supply data, and the implicit price deflator to GDP to measure inflation, the GDP and monetary policy rate. This study investigates the missing link between money supply and inflation rate in Nigeria by using the data from January 2010 to December 2018. The above serves as a hug contribution which most studies used M2 money supply and annualized time-series data.
1. INTRODUCTION
Prior to the 2008-2010 global economic and financial crises and the 2015-2017 recession in Nigeria, the Nigerian economy consistently and progressively encountered severe decades of economic and financial shock arising from the macroeconomic instability of price, money supply, non-availability and accessibility of credit among others diminishing and distorting economic growth and development in Nigeria.
Nair et al. (2018); Amiri and Talbi (2014); Kaouther and Besma (2014) reported that economic and financial shock arising from inflation, price and money supply instability, non-availability and accessibility of credit for investment were traceable to the surplus supply of money (M1, and M2) and surplus credits to private sectors. Demand-pull and cost-push inflation were end products of extreme cumulative demand pressure on production cost.
Structural inflation, especially in a mono-culture economy alike Nigeria, was traceable to the unproductive production system, lack of product value chain effect, and higgledy-piggledy circulation of products and services as a result of government policy (Nair et al., 2018).
Structural inflation directly impacts on the quality of life and living standard of the populace through government policy decreasing the supply while the demand for essential goods and services remains constant.
In the bid to prevent price and money supply instability in Nigeria and achieve money supply, credit availability, and price stability at a 2 percent inflation rate target, the monetary and fiscal policy structures were implemented (Udoh et al., 2018). Korkmaz (2018) argued that tight monetary policy frameworks geared towards achieving key economic objectives may trigger an economic recession by decreasing the aggregate demand for goods and services. Thus, various economic policy frameworks implemented by the monetary authorities in Nigeria such as a reduction in consumption demand via an interest rate increase to prevent inflation from the demand-side, or a decrease in the interest rate to prevent inflation from costs have failed to yield positive and significant results in Nigeria.
Inflation rate increased from a single digit in the 1970s to double-digits in 1990s at 63.6% and 72.8%, and the inflationary pressure on the inflation rate increased from 12.9%, in 2000 to 14% in 2001. While the headline inflation rate stayed at double digits between 15%, and 17.9% in 2002 and 2005 respectively.
The economy experienced relative stability after the 2005 economic and financial reforms translating to the merger and acquisition of banks in Nigeria. The inflation rate decelerated melodramatically to 8.24% and 5.38% in 2006 and 2007. In 2008 it increased geometrically to 11.60% and 12.00% in 2009 (Gbadebo and Mohammed, 2015).
Marginal drop in inflation occurred at 11.8% in 2010, 12.3% in 2013 and 8.1% in 2014. In 2015 it increased by 9.1% to by 15.7% in 2016 and 18.3% in the first quarters of 2017 accounting for about 100% increase in prices products and services in Nigeria (FSDH, 2016 as cited in Ditimi et al. (2017). During the 2015-2017 era of economic recession.
The money supply comprises of banknotes, and coins, outside the central bank circulating within a period of time. M0, M1, M2, and M3 measures currency and liquid instrument held in different types and sizes of account in operation within Nigeria. According to Ditimi et al. (2017) a unit growth rate in money supply increases money spread in an economy exceeding the demand for money and is defined as a direct monetary transmission mechanism (Ragan, 2014 as cited in Ditimi et al. (2017).
According to the Quantity Theory of Money inflation is triggered by the volume of money supply in an economy. It can be inferred that the increase in the volume of money supply creates credits for investment, consumption, and production to stimulate economic growth (Bello and Saulawa, 2013).
The reality in Nigeria contravenes the Quantity Theory of Money. Inflation is not a function of the money supply. In Nigeria, inflation rate is on a double digit while the rate of money supply (M2) percentage of GDP and credit to private sector percentage of GDP in the last 10 years is still on constant fluctuation as presented in Figure 1. The constant inflation rate, money supply and credit to private sector fluctuation instigate economic, social and political retardation in Nigeria and was also contributing factors to the 2015-2017 economic recession in Nigeria eroding the purchasing power of money, and the value of savings and investments in Nigeria.
The negative impact of inflation in Nigeria and the missing link triggered worry and inquiries giving birth to the question “Is money supply the cause of the high rate of inflation in Nigeria”? Or other non-monetary factors?
Figure-1. Inflation, money supply, and credit to the private sector a percentage of economic growth.
2. REVIEW OF LITERATURE
In the bid to empirically investigate whether or not money supply ganger causes high inflation in Nigeria. There is a need to address and proffer answers to a question posed by the Federal Reserve Bank of San Francisco (FRB, 2002 as cited in Ditimi et al. (2017) “on factors responsible or contributing to high rate of inflation in a nation?” Pinto (1990) as cited in Ditimi et al. (2017) observed that currency devaluation arising from the merger of official and parallel exchange rate diminishes export revenue and ganger causes inflation (Amassoma et al., 2018).
The findings of Pinto (1990) as cited in Ditimi et al. (2017) was substantiated in the studies of Egwaikhide et al. (1994); Imimole and Enoma (2011); Kaouther and Besma (2014) and Kamal (2016). The scholars underscored that currency devaluation could plausibly lead to a swift increase in the overall price level of consumer’s products via a unit increase in the production and service cost in the short-term.
Similarly, Fullerton (1993) observed that the late 1980s and 1990s currency devaluation in Nigeria, instigated other high inflation rate regimes and that inflation was induced by monetary factor without any reparations.
Bawa et al. (2016) observed that inflation exhibited a strong degree of apathy in Nigeria. The finding of Bawa et al. (2016) was buttressed in the findings of Odusanya and Atanda (2010) that GDP growth rate and inflation apathy were significant factors in explaining the inflationary process in Nigeria.
Metwally and Al- Sowaid (2004) in Egypt reported that demand-pull and cost-push were the major and core determinants of inflation. Variation in money aggregates, fiscal deficit, external sector disequilibrium, oil prices shocks, and currency devaluation spurs inflationary pressure in Nigeria and other nations. Findings from previous studies validated the submission of the monetarists’ theorem (Bozkurt, 2014).
2.1. Empirical Framework
Table-1. Empirical framework.
Author |
Scope |
Objective | Methodology | Findings |
Nigeria |
Examine the money supply to inflation from 1970 to 2016 | Co-integration and ECM approach | Lack of causality between money supply and inflation and vice versa. The lack of causality is traceable to the 2015-2017 recessions. | |
Nigeria |
Effectiveness of monetary policy on inflation | Johansen Co-integration and Error Correction Model (ECM) | Money Supply and Interest Rate significantly explained the variation in Inflation Rate. While the exchange rate is insignificant. | |
Bangladesh |
Examine the money supply on inflation from 1980 to 2014 | Granger causality and VECM approach | Unidirectional causality between budget deficit and inflation. | |
Bangladesh |
Investigate the money supply on inflation rate monthly from 2010.05-2017.12 | Co-integration and approach VECM | The money supply does not affect the inflation in short-term. There is a bi-directional causality in the long-term. | |
Indonesia |
Examine money supply on price level using monthly data from 2007.01-2017.07 | Granger causality model | There is a uni-directional causality between money supply and price level. | |
Euro Zone, countries |
Investigate the money supply on inflation | Granger causality and correlation analysis in the VAR approach | No causality between monetary aggregates and inflation. While there is causality between the balance sheet size of the commercial bank and the inflation rate. | |
GCC countries |
Examine money supply growth and inflation from 1970to 2013 | Johansen cointegration | Money supply has a long-term positive nexus on the inflation rate. | |
Pakistan |
Examine money supply growth and inflation from 1973-2013 | ARDL | Interest rate and money impact on inflation rate in the long-term while national output level in the short-term. | |
Iran |
Examine monetary variables on energy prices from 1959- 2010 | Bayesian econometric approach | A decrease in monetary variables and energy prices control the inflationary pressure in Iran. | |
India |
Examine money supply and inflation on the quantity theory of money. | Johansen cointegration and Granger causality | Inflation dynamics vary across developing economies. There is a need for a re-visit. |
3. THEORETICAL FRAMEWORK
3.1 Monetarist View
The monetarist's view is expressed as money being a function of demand-pull inflation. The quantity theory of money defines inflation as a monetary event arising from the monetary expansion of the monetary policy rate. There is a link between money supply and price level. Fisher’s exchange equation is employed to determine the link between money supply and price level.
Fisher’s exchange equation;
MV = PT
Where,
M = Currency and other financial instruments in circulation (M0, M1, M2, M3).
V = Velocity of money (measured by the sum of times money exchange hands within the economy).
P = Prevailing Price level.
T = Output level (goods and services produced).
From Fisher’s equation, it is inferred that the left-hand side of the equation symbolizes money supply while the right-hand side symbolizes demand for money. Transactions spur the demand for money. In the short-term, ‘V’ and ‘T’ are alleged to be constant and exogenously determined. P varies positively and proportionately, with M without affecting T. The rate growth in money supply positively affects the overall price level of consumer products and vice versa. A unit variation in the money supply results to the proportional change in prices.
According to the quantity theory of money to curtail inflation, in Nigeria, the volume of money in circulation must be curtailed to condense inflation in a modest way and vice versa in case of disinflation and deflation.
3.2. Criticism
The critics of the theory differ on the validity of this theory in the short-term, while others in the long-term. In Nigeria, India, and Turkey and other emerging economies the assumption of the theory vis-à-vis the constant state of “V” and “T” doesn’t hold. Specifically, in Nigeria due to other prevailing elements prevalent in the country such as political factors, double taxation, poor infrastructure, insecurity and corruption triggers inflation rather than just the money supply. The assumption is that money works in a uni-directional pattern and not in a bi-directional pattern.
A unit increase in the money supply may increase the overall price level, however, a unit decrease in the money supply may not necessarily decrease the over-all price level, a situation that is currently prevalent in Nigeria and India (Sabade, 2014).
3.3. Keynesian View
The Keynesian school of thought differs from the monetarist's view. In the short-term analysis, the Kenynsians argues that an increase in the aggregate demand increases demand-pull inflation. The gap between the aggregate demand and aggregate supply stimulates rapid inflation. The overall price levels are exogenously determined.
3.4. Structuralist View
The Structuralist school of thought explains inflation in developing countries like Nigeria. The Structuralist theory states that the demand-supply gap spurs inflation in an imperfect market with structural imbalances in some segments of the developing economies. As a result, fiscal and monetary actions can't solve this economic difficulty. The Structuralist argument forms the framework of this study to investigate the missing link in Nigeria.
3.5. Empirical Framework
Based on the findings of Mbongo et al. (2014) and Sabade (2014) in India and others, this study re-examine the money supply effect on inflation in Nigeria through a long and short-term relationship and directional causality between the variables.
4. METHODOLOGY
This study used monthly time series data from the Central Bank of Nigeria’s (CBN) Statistical Bulletin from January 2010 to December 2018 to explore the long and short-term relationship and causal link between money supply and inflation in Nigeria.
4.1. Variables
Implicit Price Deflator to GDP: measured inflation rate and is calculated as the GDP at the current basic prices divided by the GDP at the constant basic prices. The ratio explains and accounts for the change effects of inflation on the overall prices of products and services that make up the GDP.
Money Supply: M2 and M3 were used to investigate the dynamics of inflation. M3 included, M2, M1, M0 and liquid components of money supply that were not in circulation such as repurchase agreement and was the broadest measure of money supply in an economy. M2 consisted of all of M0 and M1 in addition to saving deposits and certificates of deposit.
Monetary Policy Rate (MPR): The minimum rediscounted rate (MRR) served as the CBN interest rate benchmark which anchors all other interest rates in the money market and the economy, influencing the cost of funds and its direction in the economy.
Gross Domestic Product: measures the rate of economic growth.
4.2. Model Formulation
The implicit Price Deflator to GDP was the dependent variable and the M3 and M2 money supply were explanatory variables with MPR and GDP as moderating variables.
4.2.1. The Model Expression
IPDt = f (M3t, M2t, MPRt, GDPt) (1)
IPDt = βo + β1+ β2M3t, + β3M2t, + β4MPRt, + β5GDPt + µ (2)
To take care of the out layers and for easy interpretation, the monthly datasets were Log transform following the natural log model to provide suitable coefficients of the elasticity for the dependent variable adjacent to explanatory variables. Equation 2 is transformed into:
IPDt = βo + β1+ β2LogM3t, + β3LogM2t, + β4MPRt, + β5LogGDPt + µ (3)
5. DATA AND RESULT PRESENTATION
5.1. Pre-Test
Figure-2. Variables description and characteristics.
Figure 2 describes the aggregated averages of the mean, median and standard deviation, a measure of spread and variation. Skewness measured the symmetry and kurtosis, the peakedness. The results were largely platykurtic and the kurtosis is less < 3. The JB P-value is >5%.
5.2. Unit Root
The stationarity properties of the variables were investigated by the Augmented Dickey-Fuller (ADF) and Phillips and Perron, (PP) unit root tests. The null hypothesis for the ADF and PP tests that the series has a unit root. The model expression;
Where y is the dependent variable, t is the trend, a is the intercept, µt t is white noise and p is the lag level.
Table-2. ADF and PP unit test.
Variables |
Test |
At levels @ 5% |
Inference |
Test |
1st Difference @ 5% |
Inference |
LogGDP |
ADF |
-2.475 (0.339) |
Non- Stationary |
ADF |
-7.078 (0.000)*** |
Stationary |
PP |
-3.984 (0.012) |
PP |
-14.676 (0.000) *** |
|||
LogM3 |
ADF |
-3.527 (0.045) |
Non- Stationary |
ADF |
-10.765 (0.000) *** |
Stationary |
PP |
-3.527 (0.041) |
PP |
-11.356 (0.000) *** |
|||
LogM2 |
ADF |
-3.241 (0.082) |
Non- Stationary |
ADF |
-6.311 (0.000) *** |
Stationary |
PP |
-4.441 (0.291) |
PP |
-15.133 (0.000) *** |
|||
Infr |
ADF |
-1.273 (0.883) |
Non- Stationary |
ADF |
-5.908 (0.0001) *** |
Stationary |
PP |
-2.795 (0.202) |
PP |
-14.992 (0.0000) *** |
|||
MPR |
ADF |
-2.637 (0.264) |
Non- Stationary |
ADF |
-10.373 (0.000) *** |
Stationary |
PP |
-2.637 (0.264) |
PP |
10.376 (0.0000) *** |
Note: Values in parenthesis are p-values. The asterisks *** Indicate significance at 5 %.
All the variables in Table 2 showed stationary properties at the first difference I (1). Prior to the estimation of the VECM model, it is vital to determine the lag order, using the VAR lag order selection based on these five criteria; Log-likelihood, Final prediction error (FPE), Akaike Information Criterion (AIC), Schwarz information criterion and Hannan- Quinn information criterion (HQ). The results reported that all the criteria proposed an optimal lag length of one as presented in Table 3.
Table-3. VAR lag order selection criteria.
Lag |
LogL |
LR |
FPE |
AIC |
SC |
HQ |
0 |
-41.56316 |
NA |
1.75e-06 |
0.931263 |
1.061522 |
0.983981 |
1 |
573.6945 |
1156.684* |
1.30e-11* |
-10.87389* |
-10.09234* |
-10.55758* |
2 |
574.9522 |
2.238678 |
2.11e-11 |
-10.39904 |
-8.966200 |
-9.819146 |
3 |
576.4548 |
2.524361 |
3.40e-11 |
-9.929095 |
-7.844959 |
-9.085608 |
4 |
578.2853 |
2.892288 |
5.50e-11 |
-9.465706 |
-6.730278 |
-8.358629 |
5 |
580.5703 |
3.381847 |
8.92e-11 |
-9.011407 |
-5.624686 |
-7.640740 |
6 |
583.5130 |
4.060829 |
1.45e-10 |
-8.570260 |
-4.532246 |
-6.936003 |
7 |
587.4624 |
5.055208 |
2.35e-10 |
-8.149247 |
-3.459941 |
-6.251400 |
8 |
593.0762 |
6.624302 |
3.79e-10 |
-7.761523 |
-2.420925 |
-5.600087 |
* Indicates lag order selected by the criterion.
5.3. Estimation
5.3.1. Co-Integration Analysis
The Johansen co-integration test was used to investigate the long-term equilibrium relationship among variables with the same stationarity properties. A minimum of (1) co-integrating vector wa required to established co-integration between variables.
Where:
yt, yt-1,…,yt-p = vectors of level and lagged values of P variables with the same stationarity properties;
A1,…, Ap = coefficient matrices with (PXP) dimensions;
µ = intercept vector,
εt = vector of random errors.
According to Johansen (1988) and Johansen and Juselius (1990) trace statistics are obtained by using the Eigenvalues. The trace statistic (λ trace) is estimated following the;
From the result in Table 4, the assumption of the null hypothesis of “there is no co-integrating vector” in the projected model was rejected at 5% level. Hence, there was (3) co-integrating vector in the model. The results revealed a long-term equilibrium relationship between variables of money supply and inflation in Nigeria. The results were substantiated in the Eigenvalue test results indicating (3) co-integrating equations at 5% level.
Table-4. Co-integration test.
Hypothesized |
Trace |
0.05 |
||||||
No. of CE(s) |
Eigenvalue |
Statistic |
Critical Value |
Prob.** |
||||
None* |
0.125000 |
44.00819 |
69.81889 |
0.0099 |
||||
At most 1* |
0.118903 |
30.25446 |
47.85613 |
0.0059 |
||||
At most 2* |
0.113140 |
17.21600 |
29.79707 |
0.0041 |
||||
At most 3 |
0.040691 |
4.848992 |
15.49471 |
0.8246 |
||||
At most 4 |
0.005521 |
0.570203 |
3.841466 |
0.4502 |
||||
Trace test indicates no cointegration at the 0.05 level, * denotes rejection of the hypothesis at the 0.05 level |
||||||||
Eigenvalue test |
||||||||
Hypothesized |
Max-Eigen |
0.05 |
||||||
No. of CE(s) |
Eigenvalue |
Statistic |
Critical Value |
Prob.** |
||||
None* |
0.125000 |
13.75373 |
33.87687 |
0.0099 |
||||
At most 1* |
0.118903 |
13.03846 |
27.58434 |
0.0088 |
||||
At most 2* |
0.113140 |
12.36701 |
21.13162 |
0.0059 |
||||
At most 3 |
0.040691 |
4.278788 |
14.26460 |
0.8288 |
||||
At most 4 |
0.005521 |
0.570203 |
3.841466 |
0.4502 |
||||
Max-eigenvalue test indicates no cointegration at the 0.05 level, * Denotes rejection of the hypothesis at the 0.05 level
Table-5. Vector error correction model (VECM).
Variables |
ECT (Coefficient) |
P-Value @ 5% |
CointEq1 |
-0.087 |
0.0004 |
LogGDP(-1) LogM2(-1) LogM3(-1) MPR(-1) INFR(-1) |
||
-1.169 |
0.0002 |
|
-1.654 |
0.0003 |
|
-0.038 |
0.0005 |
|
-0.003 |
0.0002 |
The ECT coefficient measures the swiftness of adjustment from disequilibrium to equilibrium as shown in Table 5. The ECT coefficient stability must be negative and significant. The CointEq1 of -0.087 was negative and significant at 5% level.
The result portrayed that disequilibrium caused by a non-monetary factor in the previous year can converge back to equilibrium at 87% in the current year. There was a long-term causality from inflation to the money supply variables.
5.4. Granger Causality Test
To determine the directional causality between the variables following co-integration analysis, the Pairwise Granger Causality test was carried out. The null hypothesis of the model was “non-causality between variables”. If the null hypothesis of the model was rejected that means the independent variable Granger-Causes the dependent variable at a 5% significance level.
The result in Table 6 indicated a uni-directional relationship between inflation and the money supply variables and a bi-directional relationship between the money supply variables and inflation was not observed in this study. Inflation granger-cause and M3 money supply, but the M2 and M3 money supply don’t granger cause inflation at the 5% significance level. Inflation reacts to the volume of money supply translating to a self-sustained rate of inflation in Nigeria. The ‘monetarist' view of inflation does not hold in Nigeria.
Table-6. Pairwise granger causality tests.
| Null Hypothesis: | Obs |
F-Statistic |
Prob. |
| LOGM2 does not Granger Cause INFR | 107 |
0.80384 |
0.172 |
| INFR does not Granger Cause LOGM2 | 0.15575 |
0.0039 |
|
| LOGM3 does not Granger Cause INFR | 107 |
0.25644 |
0.2337 |
| INFR does not Granger Cause LOGM3 | 0.06954 |
0.0025 |
|
| LOGGDP does not Granger Cause INFR | 107 |
0.0927 |
0.7614 |
| INFR does not Granger Cause LOGGDP | 0.00092 |
0.0059 |
|
| MPR does not Granger Cause INFR | 107 |
0.00511 |
0.0031 |
| INFR does not Granger Cause MPR | 0.86245 |
0.0552 |
|
| LOGM3 does not Granger Cause LOGM2 | 107 |
0.03209 |
0.8582 |
| LOGM2 does not Granger Cause LOGM3 | 1.34405 |
0.249 |
|
| LOGGDP does not Granger Cause LOGM2 | 107 |
0.19598 |
0.0089 |
| LOGM2 does not Granger Cause LOGGDP | 0.20673 |
0.6503 |
|
| MPR does not Granger Cause LOGM2 | 107 |
0.00267 |
0.9589 |
| LOGM2 does not Granger Cause MPR | 1.13725 |
0.0087 |
|
| LOGGDP does not Granger Cause LOGM3 | 107 |
0.85136 |
0.3583 |
| LOGM3 does not Granger Cause LOGGDP | 0.13526 |
0.0138 |
|
| MPR does not Granger Cause LOGM3 | 107 |
0.42041 |
0.5182 |
| LOGM3 does not Granger Cause MPR | 0.98909 |
0.3223 |
|
| MPR does not Granger Cause LOGGDP | 107 |
0.02195 |
0.8825 |
| LOGGDP does not Granger Cause MPR | 0.87588 |
0.0015 |
|
The finding of this study supported the findings of Nair et al. (2018); Taslim (1982) and Chowdhury et al. (1995) in Bangladesh, Fabian and Charles (2014) in Nigeria, Rakić and Rađenović (2013) in Serbia among others. Inflation is not a function of M2 and M3 money supply in Nigeria. The findings of this vary from studies of Adodo et al. (2018); Dania (2013); Iya and Aminu (2014) in Nigeria that reported inflation as a function of the money supply. This study opposed the study of Akinbobola (2012) in Nigeria that inflation and money supply had no explanation. The study of Akinbobola (2012) ignored other non-monetary factors in Nigeria which have a ripple effect on the economy.
6. CONCLUSION
The result of the Johansen cointegration test showed a long-term relationship between the money supply variables and inflation. The VECM result showed that disequilibrium caused by a non-monetary factor such as the money supply in the previous year can converge back to equilibrium at 87% in the current year. The directional causality test reported a bi-directional causality between inflation and the M2 and M3 money supply variables. It has been established that monetary factors do not affect the price level through inflation in Nigeria, but that non-monetary factors of political instability, corruption, double taxation, and poor infrastructure development among others does. This study recommends that non-monetary factors should be constrained and put in suitable perspective to achieve a low inflation at single digits at most.
| Funding: This study received no specific financial support. |
| Competing Interests: The authors declare that they have no competing interests. |
| Acknowledgement: All authors contributed equally to the conception and design of the study. |
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